A matrix method was developed to examine functional interactions between brain regions, by correlating regional cerebral metabolic rates for glucose as determined by positron emission tomography in humans. The method was applied to regional metabolic data from 14 young adult patients with Down Syndrome and 24 matched control subjects. Compared with controls, the Down syndrome group had many correlations within and between the frontal and parietal lobes with lower values, as well as many correlations between the thalamus and cortex with reduced values. These results indicate a disruption of neural systems associated with attention in Down Syndrome. The matrix method was applied to analyze glucose metabolism in awake Fischer-344 rats. Reduced correlations between left and right hemispheric brain regions were found in rats that had undergone corpus callosotomies, suggesting that interhemispheric interactions are mediated in part by callosal fibers. A computer simulation model was developed for the purpose of giving a partial validation for correlational analysis as applied to metabolic data. Because the underlying pattern of functional couplings in the model is known, these simulations demonstrate that the correlation coefficient between normalized metabolic rates is proportional to the strength of the functional coupling constant, and that correlational analysis yields information on regional involvement in neural systems not evident in the pattern of absolute metabolic values.